Abstract
OBJECTIVES: Test performance is conventionally expressed by gain in diagnostic certainty. We propose net diagnostic gain and indication area as more appropriate measures of test performance; then, the loss in certainty due to misclassification and the information of "no test" would be performed are taken into account. STUDY DESIGN AND SETTING: A decision analytical model was developed in which two alternative strategies were compared: testing and no testing. Correct diagnostic test results received a positive value; undesired test results received a negative value. Within the "no test" scenario, it was assumed that physicians are more prone to treat as the probability of disease is higher. RESULTS: Discounting gain and loss in diagnostic certainty results in a concave function of the prior. The indication area is the range of priors with a net diagnostic gain; testing is deleterious beyond this range. The net diagnostic gain reaches a maximum at a specific prior. A freely available Web site-based calculator was developed for easy calculation of the indication area and the maximum diagnostic gain for each combination of sensitivity and specificity. CONCLUSION: Medical testing is not indicated when the prior disease probabilities are low (as to screening for a condition) or high (for diagnostic confirmation).
